Week 2: Filled with papers, maps, and stories of misadventures in the field.

June 18th, 2017

It’s the end of week two of the internship, and I’ve done my best to hit the ground running, and keep moving. In these nine days, I’ve looked at over 2,000 seismographs (and we’re just getting started!), and read 10 scientific papers on shear wave splitting and Mount St Helens. To be honest, I was expecting to read a decent number of papers, but I wasn’t really prepared for how intellectually engaged you have to be while reading them; you can’t just gloss over sections and expect to fully understand all of the writer’s main points. When I mentioned this to my dad, a retired OU professor, he just laughed and said, “Well, yeah. That’s part of the business!” Knowing that this of course would be a part of my summer, I could only reply with “touché.”

I’ve also started to learn to code in Python, and have managed to make a couple of maps. I think they look pretty nice! I’ve put them in this post below, so you can judge for yourself if they deserve a spot on the AGU research poster.

The maps are of the seismometer stations deployed around Mount St. Helens. The red triangles are the four broadband stations that are continually collecting data on the mountain (one of them had recorded > 800 magnitude 6+ earthquakes!!), and the green diamonds are the iMUSH stations, which is where we’re getting the majority of the data for this project.

The iMUSH stations were deployed as a part of the iMUSH (Imaging Magma Under St. Helens) experiment in 2014. On the whole, they comprised an array of seismometers that passively collected earthquake data for 2 years. Deploying them, and then retrieving them later, turned out to be quite a challenge! I talked to Dr. Ken Creager, and Carl Ulberg, two of the people heavily involved in the iMUSH project about the experiment, and they were all too happy to share some stories. At each of the 70 locations, the deployers had to dig a hole for the seismometer, place said seismometer in a “vault” that was then put into the hole and cemented in the ground, then set up a digital recording system, as well as a solar panel to power the whole thing. Dr. Steve Malone, another professor at the University of Washington, posted quite often in the blog for the experiment, and explains the process of deploying stations very well (and with pictures!) here: http://imush.org/blog/2014/06/22/a-day-in-the-life

While deploying was rough, sometimes it was difficult for the instruments to stay operational in the field, due to natural or human interference. Dr. Creager had a lot of good stories about these ‘interruptions!’ One concerned local apparently also saw a station and reported it to the FDA, saying that the setup was most likely a meth lab. The FDA phoned Dr. Creager about the seismometer, and proceeded to take apart the entire setup, and left everything there in pieces. I can only imagine what a strange phone call that was… Another site actually caught fire, and when the researchers came to extract the data and equipment, they only found the charred remains of a breakout box, solar panel, and seismometer. (I’ve put in a pic of the box, too. It was pretty incredible.)

On the left is what used to be a car battery, which provides power to the operation, and is normally supplemented by the solar panel. The other parts include a power monitor, a recording system, and a lot of wires.

Nevertheless, the experiment has yielded some very good data, and some results have already been published! (Hansen et al. 2016, Kiser et al. 2016). My part of this project will be doing a shear wave splitting analysis of local S waves just below the mountain, as well as SKS waves that travel through the core, all of the mantle, and then the crust to the stations. I’m pretty lucky, because there is already a program called SplitLab that makes these measurements relatively painless. I think the hardest things will be determining the criteria for which we’ll do the analysis. We’ll have to choose earthquakes to view based on their magnitude and place of origin. We’ll also have to figure out exactly how we want to filter the data, something that will almost definitely be different for the S wave analysis and the SKS wave analysis. Despite these small weaknesses, I’m really excited to dive into this dataset! What is really neat about my part of the iMUSH project is that shear wave splitting analysis hasn’t actually been done on any volcanoes in this region, and definitely not with such a dense array of instruments. With any luck, we’ll find out some really cool things about the anisotropy of the volcano!

During this coming week, there will be a small convention of everyone working with the iMUSH data, and I’m lucky enough that I also get to go and see what everyone else has been doing with the data and learning about Mount St Helens. I hope that this will end up being a good opportunity to practice explaining my research to other scientists in a comprehensible manner. This task includes talking about where the data came from, what specific parts of the dataset will be used, what the measurements tell us about the volcano, and how those inferences relate to the geology of the region. More importantly, it includes saying all of those things in a way that is easy to follow and understand. As an undergraduate, this is not something that I am not used to doing, but it was pointed out to me, and the rest of the IRIS interns that it is definitely an important skill to have, for obvious reasons. Hopefully this convention (and this blog) will help me hone that skill!

Anyway, that's all of my updates for now, I guess. I don't have a funny story about me tramping around a stranger's backyard for this post, but I'll what kind of trouble I can get into for next week!

Cheers,

Abe

Comments

Abe, did you make the maps in Python? If so, what module did you use? Just curious because I am much more comfortable with Python than GMT and so would prefer to use Python when it comes time for me to start making maps.

Jonah, I used the basemap module to make the actual map, and obspy to fetch the station names and locations. There's this great function in basemap that just let's you pull images straight from ArcGIS servers, which is super convenient. Erin convinced me to download the Anaconda navigator for python, which it makes finding and implementing new modules really easy.

I wasn't aware of the baseman module. That's probably the piece of info that I was looking for. I don't need it yet, but it will almost certainly come in handy later. As far as general Python goes, I wouldn't go through any method of installation except for Anaconda. You get all the packages you need, updating is easy, and it is so clean.